Articles | Volume 2, issue 1
https://doi.org/10.5194/wes-2-295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/wes-2-295-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Jun 2017
Research article |
| 02 Jun 2017
Atmospheric turbulence affects wind turbine nacelle transfer functions
Clara M. St. Martin
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences (ATOC), University of
Colorado at Boulder, 311 UCB, Boulder, CO 80309, USA
Julie K. Lundquist
Department of Atmospheric and Oceanic Sciences (ATOC), University of
Colorado at Boulder, 311 UCB, Boulder, CO 80309, USA
National Renewable Energy Laboratory, 15013 Denver West Parkway,
Golden, CO 80401, USA
Andrew Clifton
National Renewable Energy Laboratory, 15013 Denver West Parkway,
Golden, CO 80401, USA
Gregory S. Poulos
V-Bar, LLC, 1301 Arapahoe Street, Suite 105, Golden, CO 80401, USA
Scott J. Schreck
National Renewable Energy Laboratory, 15013 Denver West Parkway,
Golden, CO 80401, USA
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Cited
27 citations as recorded by crossref.
- Wind Turbine Multivariate Power Modeling Techniques for Control and Monitoring Purposes D. Astolfi et al. https://doi.org/10.1115/1.4048490
- Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement H. Kim & J. Kim https://doi.org/10.3390/en14082319
- An experimental study on the shape of the nacelle transfer function under different inflow and operating conditions N. Devalckeneer et al. https://doi.org/10.1088/1742-6596/3224/4/042044
- The 15-year operational experiences of an 850 kW peri-urban wind turbine: Lessons learned from a behind-the-meter installation in Ireland R. Byrne & P. MacArtain https://doi.org/10.1016/j.esd.2022.08.011
- Integration of System Level CFD Simulations into the Development Process of Wind Turbine Prototypes M. Arnold et al. https://doi.org/10.1088/1742-6596/1618/5/052007
- Wind Turbine Response in Waked Inflow: A Modelling Benchmark Against Full-Scale Measurements H. Asmuth et al. https://doi.org/10.2139/ssrn.3940154
- Diagnosis of wind turbine systematic yaw error through nacelle anemometer measurement analysis D. Astolfi et al. https://doi.org/10.1016/j.segan.2023.101071
- Evaluation of wind speed estimates in reanalyses for wind energy applications S. Brune et al. https://doi.org/10.5194/asr-18-115-2021
- The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality T. McCandless & S. Haupt https://doi.org/10.5194/wes-4-343-2019
- Assessing the effects of anemometer systematic errors on wind generators performance by data-driven techniques D. Astolfi et al. https://doi.org/10.1016/j.segan.2024.101417
- Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements H. Asmuth et al. https://doi.org/10.1016/j.renene.2022.04.047
- Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression D. Astolfi & R. Pandit https://doi.org/10.3390/app12010072
- Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind Z. Wu et al. https://doi.org/10.1002/we.2477
- Development of a novel method for the correction of the nacelle wind speed in stall-controlled wind turbines L. Vivas et al. https://doi.org/10.1088/1742-6596/2767/3/032008
- Snow-powered research on utility-scale wind turbine flows J. Hong & A. Abraham https://doi.org/10.1007/s10409-020-00934-7
- Wind Turbine Power Curve Monitoring Based on Environmental and Operational Data S. Cascianelli et al. https://doi.org/10.1109/TII.2021.3128205
- Fleet-Wide Knowledge-Discovery-Based Methods for Wind Turbine Performance Monitoring: A Test Case Discussion D. Astolfi et al. https://doi.org/10.1007/s40866-025-00275-z
- Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project J. Zhang et al. https://doi.org/10.3390/en16052193
- How accurate is nacelle-based anemometry during intentional yaw misalignment? An experimental assessment from a near-ideal site T. Vanelli et al. https://doi.org/10.1088/1742-6596/3224/2/022026
- LiDAR-Referenced Inflow Wind Condition Estimation from SCADA Data Using a Deep Learning Model S. He et al. https://doi.org/10.3390/en19051373
- An interpretable data-driven intelligent prediction framework for wind turbine wake turbulence intensity based on machine learning model Z. Li et al. https://doi.org/10.1016/j.engstruct.2026.122916
- Development and validation of a hybrid data-driven model-based wake steering controller and its application at a utility-scale wind plant P. Bachant et al. https://doi.org/10.5194/wes-9-2235-2024
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi https://doi.org/10.3390/machines9050100
- The impact of far-reaching offshore cluster wakes on wind turbine fatigue loads A. Anantharaman et al. https://doi.org/10.5194/wes-10-1849-2025
- Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring D. Astolfi et al. https://doi.org/10.3390/en14041105
- False alarm detection in wind turbine by classification models A. Peco Chacón et al. https://doi.org/10.1016/j.advengsoft.2023.103409
- Wind Turbine Operation Curves Modelling Techniques D. Astolfi https://doi.org/10.3390/electronics10030269
27 citations as recorded by crossref.
- Wind Turbine Multivariate Power Modeling Techniques for Control and Monitoring Purposes D. Astolfi et al. https://doi.org/10.1115/1.4048490
- Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement H. Kim & J. Kim https://doi.org/10.3390/en14082319
- An experimental study on the shape of the nacelle transfer function under different inflow and operating conditions N. Devalckeneer et al. https://doi.org/10.1088/1742-6596/3224/4/042044
- The 15-year operational experiences of an 850 kW peri-urban wind turbine: Lessons learned from a behind-the-meter installation in Ireland R. Byrne & P. MacArtain https://doi.org/10.1016/j.esd.2022.08.011
- Integration of System Level CFD Simulations into the Development Process of Wind Turbine Prototypes M. Arnold et al. https://doi.org/10.1088/1742-6596/1618/5/052007
- Wind Turbine Response in Waked Inflow: A Modelling Benchmark Against Full-Scale Measurements H. Asmuth et al. https://doi.org/10.2139/ssrn.3940154
- Diagnosis of wind turbine systematic yaw error through nacelle anemometer measurement analysis D. Astolfi et al. https://doi.org/10.1016/j.segan.2023.101071
- Evaluation of wind speed estimates in reanalyses for wind energy applications S. Brune et al. https://doi.org/10.5194/asr-18-115-2021
- The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality T. McCandless & S. Haupt https://doi.org/10.5194/wes-4-343-2019
- Assessing the effects of anemometer systematic errors on wind generators performance by data-driven techniques D. Astolfi et al. https://doi.org/10.1016/j.segan.2024.101417
- Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements H. Asmuth et al. https://doi.org/10.1016/j.renene.2022.04.047
- Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression D. Astolfi & R. Pandit https://doi.org/10.3390/app12010072
- Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind Z. Wu et al. https://doi.org/10.1002/we.2477
- Development of a novel method for the correction of the nacelle wind speed in stall-controlled wind turbines L. Vivas et al. https://doi.org/10.1088/1742-6596/2767/3/032008
- Snow-powered research on utility-scale wind turbine flows J. Hong & A. Abraham https://doi.org/10.1007/s10409-020-00934-7
- Wind Turbine Power Curve Monitoring Based on Environmental and Operational Data S. Cascianelli et al. https://doi.org/10.1109/TII.2021.3128205
- Fleet-Wide Knowledge-Discovery-Based Methods for Wind Turbine Performance Monitoring: A Test Case Discussion D. Astolfi et al. https://doi.org/10.1007/s40866-025-00275-z
- Applicability of WorldCover in Wind Power Engineering: Application Research of Coupled Wake Model Based on Practical Project J. Zhang et al. https://doi.org/10.3390/en16052193
- How accurate is nacelle-based anemometry during intentional yaw misalignment? An experimental assessment from a near-ideal site T. Vanelli et al. https://doi.org/10.1088/1742-6596/3224/2/022026
- LiDAR-Referenced Inflow Wind Condition Estimation from SCADA Data Using a Deep Learning Model S. He et al. https://doi.org/10.3390/en19051373
- An interpretable data-driven intelligent prediction framework for wind turbine wake turbulence intensity based on machine learning model Z. Li et al. https://doi.org/10.1016/j.engstruct.2026.122916
- Development and validation of a hybrid data-driven model-based wake steering controller and its application at a utility-scale wind plant P. Bachant et al. https://doi.org/10.5194/wes-9-2235-2024
- Perspectives on SCADA Data Analysis Methods for Multivariate Wind Turbine Power Curve Modeling D. Astolfi https://doi.org/10.3390/machines9050100
- The impact of far-reaching offshore cluster wakes on wind turbine fatigue loads A. Anantharaman et al. https://doi.org/10.5194/wes-10-1849-2025
- Multivariate SCADA Data Analysis Methods for Real-World Wind Turbine Power Curve Monitoring D. Astolfi et al. https://doi.org/10.3390/en14041105
- False alarm detection in wind turbine by classification models A. Peco Chacón et al. https://doi.org/10.1016/j.advengsoft.2023.103409
- Wind Turbine Operation Curves Modelling Techniques D. Astolfi https://doi.org/10.3390/electronics10030269
Saved (final revised paper)
Latest update: 03 Jun 2026
Short summary
We use upwind and nacelle-based measurements from a wind turbine and investigate the influence of atmospheric stability and turbulence regimes on nacelle transfer functions (NTFs) used to correct nacelle-mounted anemometer measurements. This work shows that correcting nacelle winds using NTFs results in similar energy production estimates to those obtained using upwind tower-based wind speeds. Further, stability and turbulence metrics have been found to have an effect on NTFs below rated speed.
We use upwind and nacelle-based measurements from a wind turbine and investigate the influence...
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